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Modelling and examining the influence of predictor variables on the road crashes in functionally classified vehicles in Pakistan
International Journal of Crashworthiness ( IF 1.9 ) Pub Date : 2021-04-19 , DOI: 10.1080/13588265.2021.1909839
Muhammad Hussain 1 , Jing Shi 1
Affiliation  

Abstract

This paper deals with the modelling and examination of the influence of predictor variables (contributory factors) on road crashes (RCs) among functionally classified vehicles (i) motorcycles, (ii) non-commercial (private) vehicles, and (iii) commercial (work-related vehicles) in Pakistan. A retrospective study was performed on the RC data (2013-2017), collected from the National Highway and Motorway Police (NHMP) in Pakistan. A multinomial logit model was developed to examine the risk of RCs in three distinct functionally classified vehicles based on contributory factors. The contributory factors in this study belong to four major categories: crash characteristics (crash severity, weekday indicator, weekend indicator, tourist season), driver characteristics (careless driving, fatigue driving, speeding), vehicle characteristics (mechanical fault, tire bursts), and road characteristics (poor road conditions). The findings of this study provide evidence of RCs caused by careless driving, fatigue driving, speeding, tire burst, poor road conditions, mechanical failure, and crash severity associated with different functionally classified vehicles. Among all the predictor variables, RCs caused by careless driving, speeding, and poor road conditions were significantly associated with motorcycles than commercial drivers. Whereas, RCs caused by fatigue driving and mechanical fault were more prevalent in commercial vehicles as compared to non-commercial vehicles and motorcycles. Tire bursts and crash severity were found to be significant predictors of RCs in non-commercial vehicles. The results could apply to designing and implementing a crash prevention system that could minimise the risk of accidents between vehicles of different types in Pakistan and countries with similar road safety challenges.



中文翻译:

建模和检查预测变量对巴基斯坦功能分类车辆道路碰撞的影响

摘要

本文讨论了预测变量(贡献因素)对功能分类车辆(i)摩托车、(ii)非商业(私人)车辆和(iii)商业(工作相关车辆)在巴基斯坦。对从巴基斯坦国家公路和高速公路警察 (NHMP) 收集的 RC 数据 (2013-2017) 进行了回顾性研究。开发了多项 logit 模型,以根据影响因素检查三种不同功能分类车辆中 RC 的风险。本研究的影响因素分为四大类:碰撞特征(碰撞严重程度、工作日指标、周末指标、旅游旺季)、驾驶员特征(粗心驾驶、疲劳驾驶、超速)、车辆特征(机械故障、爆胎)和道路特性(路况不佳)。这项研究的结果提供了与不同功能分类车辆相关的粗心驾驶、疲劳驾驶、超速、爆胎、恶劣路况、机械故障和碰撞严重程度引起的 RC 的证据。在所有预测变量中,粗心驾驶、超速和恶劣路况引起的 RC 与摩托车的相关性显着高于商业司机。然而,与非商用车辆和摩托车相比,由疲劳驾驶和机械故障引起的 RC 在商用车辆中更为普遍。发现轮胎爆裂和碰撞严重程度是非商用车辆 RC 的重要预测因素。

更新日期:2021-04-19
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